Overview

Dataset statistics

Number of variables20
Number of observations295524
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.1 MiB
Average record size in memory160.0 B

Variable types

Numeric20

Alerts

CO (ppm) is highly overall correlated with Time (s) and 9 other fieldsHigh correlation
Humidity (%r.h.) is highly overall correlated with Time (s) and 2 other fieldsHigh correlation
Temperature (C) is highly overall correlated with Time (s) and 2 other fieldsHigh correlation
Heater voltage (V) is highly overall correlated with R4 (MOhm) and 9 other fieldsHigh correlation
R1 (MOhm) is highly overall correlated with R2 (MOhm) and 8 other fieldsHigh correlation
R2 (MOhm) is highly overall correlated with R1 (MOhm) and 6 other fieldsHigh correlation
R3 (MOhm) is highly overall correlated with R1 (MOhm) and 5 other fieldsHigh correlation
R4 (MOhm) is highly overall correlated with Heater voltage (V) and 13 other fieldsHigh correlation
R5 (MOhm) is highly overall correlated with Heater voltage (V) and 13 other fieldsHigh correlation
R6 (MOhm) is highly overall correlated with R1 (MOhm) and 11 other fieldsHigh correlation
R7 (MOhm) is highly overall correlated with Heater voltage (V) and 13 other fieldsHigh correlation
R8 (MOhm) is highly overall correlated with CO (ppm) and 11 other fieldsHigh correlation
R9 (MOhm) is highly overall correlated with CO (ppm) and 12 other fieldsHigh correlation
R10 (MOhm) is highly overall correlated with CO (ppm) and 11 other fieldsHigh correlation
R11 (MOhm) is highly overall correlated with CO (ppm) and 10 other fieldsHigh correlation
R12 (MOhm) is highly overall correlated with CO (ppm) and 13 other fieldsHigh correlation
R13 (MOhm) is highly overall correlated with CO (ppm) and 12 other fieldsHigh correlation
R14 (MOhm) is highly overall correlated with CO (ppm) and 11 other fieldsHigh correlation
Time (s) is highly overall correlated with CO (ppm) and 2 other fieldsHigh correlation
Flow rate (mL/min) is highly skewed (γ1 = -101.2673158)Skewed
Time (s) is uniformly distributedUniform
Time (s) has unique valuesUnique
CO (ppm) has 32188 (10.9%) zerosZeros

Reproduction

Analysis started2022-12-20 08:37:33.225145
Analysis finished2022-12-20 08:39:26.634775
Duration1 minute and 53.41 seconds
Software versionpandas-profiling vv3.5.0
Download configurationconfig.json

Variables

Time (s)
Real number (ℝ)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct295524
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45467.083
Minimum0
Maximum90909.588
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:26.794955image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4547.8514
Q122760.241
median45478.334
Q368198.19
95-th percentile86365.708
Maximum90909.588
Range90909.588
Interquartile range (IQR)45437.949

Descriptive statistics

Standard deviation26242.884
Coefficient of variation (CV)0.57718424
Kurtosis-1.1998183
Mean45467.083
Median Absolute Deviation (MAD)22719.05
Skewness-0.0010804931
Sum1.3436614 × 1010
Variance6.8868895 × 108
MonotonicityStrictly increasing
2022-12-20T14:09:27.004968image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
60659.193 1
 
< 0.1%
60630.765 1
 
< 0.1%
60630.456 1
 
< 0.1%
60630.147 1
 
< 0.1%
60629.838 1
 
< 0.1%
60629.53 1
 
< 0.1%
60629.22 1
 
< 0.1%
60628.911 1
 
< 0.1%
60628.602 1
 
< 0.1%
Other values (295514) 295514
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
0.31 1
< 0.1%
0.619 1
< 0.1%
0.927 1
< 0.1%
1.236 1
< 0.1%
1.544 1
< 0.1%
1.853 1
< 0.1%
2.161 1
< 0.1%
2.468 1
< 0.1%
2.778 1
< 0.1%
ValueCountFrequency (%)
90909.588 1
< 0.1%
90909.279 1
< 0.1%
90908.971 1
< 0.1%
90908.663 1
< 0.1%
90908.353 1
< 0.1%
90908.044 1
< 0.1%
90907.735 1
< 0.1%
90907.427 1
< 0.1%
90907.117 1
< 0.1%
90906.81 1
< 0.1%

CO (ppm)
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct305
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8996143
Minimum0
Maximum20
Zeros32188
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:27.283500image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.44
median8.89
Q315.56
95-th percentile20
Maximum20
Range20
Interquartile range (IQR)11.12

Descriptive statistics

Standard deviation6.4287822
Coefficient of variation (CV)0.64939724
Kurtosis-1.233895
Mean9.8996143
Median Absolute Deviation (MAD)6.67
Skewness0.0093150247
Sum2925573.6
Variance41.329241
MonotonicityNot monotonic
2022-12-20T14:09:27.460051image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32188
10.9%
17.78 29276
9.9%
8.89 29268
9.9%
6.67 29263
9.9%
4.44 29230
9.9%
15.56 29228
9.9%
13.33 29225
9.9%
20 29224
9.9%
2.22 29219
9.9%
11.11 29106
9.8%
Other values (295) 297
 
0.1%
ValueCountFrequency (%)
0 32188
10.9%
0.2666 1
 
< 0.1%
0.404 2
 
< 0.1%
0.5217 1
 
< 0.1%
0.5905 1
 
< 0.1%
0.5999 1
 
< 0.1%
0.667 1
 
< 0.1%
0.6934 1
 
< 0.1%
0.8179 1
 
< 0.1%
1.14 1
 
< 0.1%
ValueCountFrequency (%)
20 29224
9.9%
19.9334 1
 
< 0.1%
19.818 1
 
< 0.1%
19.64 1
 
< 0.1%
19.627 1
 
< 0.1%
19.5911 1
 
< 0.1%
19.2563 1
 
< 0.1%
18.5792 1
 
< 0.1%
18.4504 1
 
< 0.1%
18.2595 1
 
< 0.1%

Humidity (%r.h.)
Real number (ℝ)

Distinct18684
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.019333
Minimum16.39
Maximum71.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:27.643042image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum16.39
5-th percentile22.53
Q135.59
median46.11
Q354.79
95-th percentile64.22
Maximum71.96
Range55.57
Interquartile range (IQR)19.2

Descriptive statistics

Standard deviation12.364203
Coefficient of variation (CV)0.27464207
Kurtosis-0.72469097
Mean45.019333
Median Absolute Deviation (MAD)9.46
Skewness-0.15852084
Sum13304293
Variance152.87351
MonotonicityNot monotonic
2022-12-20T14:09:27.799073image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.91 5491
 
1.9%
21.97 4893
 
1.7%
37.19 4299
 
1.5%
31.83 4193
 
1.4%
50.74 4067
 
1.4%
30.75 3882
 
1.3%
45.59 3594
 
1.2%
49.73 3308
 
1.1%
46.63 3224
 
1.1%
43.51 3203
 
1.1%
Other values (18674) 255370
86.4%
ValueCountFrequency (%)
16.39 863
0.3%
16.3901 1
 
< 0.1%
16.3904 1
 
< 0.1%
16.3908 1
 
< 0.1%
16.3917 1
 
< 0.1%
16.5247 1
 
< 0.1%
16.5655 1
 
< 0.1%
16.6957 1
 
< 0.1%
16.7382 1
 
< 0.1%
16.8662 1
 
< 0.1%
ValueCountFrequency (%)
71.96 608
0.2%
71.9598 2
 
< 0.1%
71.9595 2
 
< 0.1%
71.9592 2
 
< 0.1%
71.9461 1
 
< 0.1%
71.9165 1
 
< 0.1%
71.8972 1
 
< 0.1%
71.8738 1
 
< 0.1%
71.7986 1
 
< 0.1%
71.7681 1
 
< 0.1%

Temperature (C)
Real number (ℝ)

Distinct2776
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.336311
Minimum26.14
Maximum26.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:27.970604image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum26.14
5-th percentile26.22
Q126.3
median26.34
Q326.38
95-th percentile26.46
Maximum26.5
Range0.36
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.074718757
Coefficient of variation (CV)0.0028371004
Kurtosis-0.74319313
Mean26.336311
Median Absolute Deviation (MAD)0.04
Skewness-0.18197392
Sum7783012
Variance0.0055828927
MonotonicityNot monotonic
2022-12-20T14:09:28.136428image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.38 62532
21.2%
26.3 61366
20.8%
26.34 38923
13.2%
26.42 30461
10.3%
26.22 29095
9.8%
26.46 26583
9.0%
26.26 21287
 
7.2%
26.18 9178
 
3.1%
26.3001 442
 
0.1%
26.3399 439
 
0.1%
Other values (2766) 15218
 
5.1%
ValueCountFrequency (%)
26.14 173
0.1%
26.1401 4
 
< 0.1%
26.1408 1
 
< 0.1%
26.1411 1
 
< 0.1%
26.1419 1
 
< 0.1%
26.142 1
 
< 0.1%
26.1424 1
 
< 0.1%
26.1426 1
 
< 0.1%
26.1434 1
 
< 0.1%
26.1437 1
 
< 0.1%
ValueCountFrequency (%)
26.5 52
< 0.1%
26.4993 1
 
< 0.1%
26.4989 1
 
< 0.1%
26.4975 1
 
< 0.1%
26.4951 1
 
< 0.1%
26.4943 1
 
< 0.1%
26.4896 1
 
< 0.1%
26.4881 1
 
< 0.1%
26.4877 1
 
< 0.1%
26.4869 1
 
< 0.1%

Flow rate (mL/min)
Real number (ℝ)

Distinct11423
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239.94339
Minimum0
Maximum272.8193
Zeros8
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:28.422168image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile239.7516
Q1239.8952
median239.972
Q3240.0455
95-th percentile240.18389
Maximum272.8193
Range272.8193
Interquartile range (IQR)0.1503

Descriptive statistics

Standard deviation1.8934362
Coefficient of variation (CV)0.0078911787
Kurtosis11868.472
Mean239.94339
Median Absolute Deviation (MAD)0.0752
Skewness-101.26732
Sum70909030
Variance3.5851005
MonotonicityNot monotonic
2022-12-20T14:09:28.571877image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
239.9789 146
 
< 0.1%
239.9889 139
 
< 0.1%
239.9769 135
 
< 0.1%
239.9658 135
 
< 0.1%
239.9771 133
 
< 0.1%
239.9788 133
 
< 0.1%
239.9368 132
 
< 0.1%
239.962 131
 
< 0.1%
239.9913 131
 
< 0.1%
239.9436 131
 
< 0.1%
Other values (11413) 294178
99.5%
ValueCountFrequency (%)
0 8
< 0.1%
0.154 1
 
< 0.1%
0.5958 1
 
< 0.1%
1.0406 1
 
< 0.1%
9.0692 1
 
< 0.1%
18.8232 1
 
< 0.1%
60.0295 1
 
< 0.1%
82.7453 1
 
< 0.1%
92.1943 1
 
< 0.1%
101.6187 1
 
< 0.1%
ValueCountFrequency (%)
272.8193 1
< 0.1%
264.8978 1
< 0.1%
262.6104 1
< 0.1%
261.5421 1
< 0.1%
260.6414 1
< 0.1%
260.4117 1
< 0.1%
260.2719 1
< 0.1%
255.5868 1
< 0.1%
255.4439 1
< 0.1%
255.3575 1
< 0.1%

Heater voltage (V)
Real number (ℝ)

Distinct1720
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.35484758
Minimum0.198
Maximum0.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:28.738460image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.198
5-th percentile0.1991
Q10.2
median0.2
Q30.2069
95-th percentile0.898
Maximum0.9
Range0.702
Interquartile range (IQR)0.0069

Descriptive statistics

Standard deviation0.28835765
Coefficient of variation (CV)0.81262397
Kurtosis-0.20592393
Mean0.35484758
Median Absolute Deviation (MAD)0.0003
Skewness1.3370905
Sum104865.98
Variance0.083150132
MonotonicityNot monotonic
2022-12-20T14:09:28.898411image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 127801
43.2%
0.898 33851
 
11.5%
0.199 12893
 
4.4%
0.1993 6390
 
2.2%
0.1996 6309
 
2.1%
0.1998 6302
 
2.1%
0.1992 6281
 
2.1%
0.1995 6272
 
2.1%
0.1997 6262
 
2.1%
0.1994 6249
 
2.1%
Other values (1710) 76914
26.0%
ValueCountFrequency (%)
0.198 1
 
< 0.1%
0.1981 4
< 0.1%
0.1982 5
< 0.1%
0.1983 7
< 0.1%
0.1984 5
< 0.1%
0.1985 7
< 0.1%
0.1986 2
 
< 0.1%
0.1987 2
 
< 0.1%
0.1988 3
 
< 0.1%
0.1989 9
< 0.1%
ValueCountFrequency (%)
0.9 1
 
< 0.1%
0.8998 2
 
< 0.1%
0.8997 2
 
< 0.1%
0.8995 1
 
< 0.1%
0.8994 1
 
< 0.1%
0.8993 1
 
< 0.1%
0.8991 1
 
< 0.1%
0.899 1723
0.6%
0.8989 1042
0.4%
0.8988 1084
0.4%

R1 (MOhm)
Real number (ℝ)

Distinct8488
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.279101
Minimum0.0327
Maximum116.4568
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:29.079561image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0327
5-th percentile0.0788
Q10.4204
median1.9655
Q328.6645
95-th percentile69.1448
Maximum116.4568
Range116.4241
Interquartile range (IQR)28.2441

Descriptive statistics

Standard deviation23.669193
Coefficient of variation (CV)1.4539619
Kurtosis0.86066447
Mean16.279101
Median Absolute Deviation (MAD)1.8836
Skewness1.4186521
Sum4810865.1
Variance560.23068
MonotonicityNot monotonic
2022-12-20T14:09:29.247950image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.9176 768
 
0.3%
70.2486 743
 
0.3%
73.1111 726
 
0.2%
69.1448 715
 
0.2%
71.3877 707
 
0.2%
72.5638 706
 
0.2%
73.7788 705
 
0.2%
70.7619 694
 
0.2%
68.0747 690
 
0.2%
68.5571 667
 
0.2%
Other values (8478) 288403
97.6%
ValueCountFrequency (%)
0.0327 2
 
< 0.1%
0.0328 1
 
< 0.1%
0.0331 1
 
< 0.1%
0.0335 1
 
< 0.1%
0.0336 1
 
< 0.1%
0.0338 5
< 0.1%
0.0339 1
 
< 0.1%
0.0341 1
 
< 0.1%
0.0344 1
 
< 0.1%
0.0346 1
 
< 0.1%
ValueCountFrequency (%)
116.4568 2
 
< 0.1%
114.818 4
 
< 0.1%
113.4868 5
 
< 0.1%
111.9292 10
 
< 0.1%
110.6632 17
 
< 0.1%
109.181 22
< 0.1%
107.9756 23
< 0.1%
106.5634 41
< 0.1%
105.4143 32
< 0.1%
104.0673 54
< 0.1%

R2 (MOhm)
Real number (ℝ)

Distinct8241
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.270412
Minimum0.0571
Maximum138.1101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:29.421117image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0571
5-th percentile0.1403
Q10.4931
median1.4924
Q332.1377
95-th percentile78.3034
Maximum138.1101
Range138.053
Interquartile range (IQR)31.6446

Descriptive statistics

Standard deviation27.345841
Coefficient of variation (CV)1.4967282
Kurtosis0.33743925
Mean18.270412
Median Absolute Deviation (MAD)1.3504
Skewness1.3352752
Sum5399345.2
Variance747.79501
MonotonicityNot monotonic
2022-12-20T14:09:29.583220image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79.7171 1133
 
0.4%
82.004 1123
 
0.4%
78.3034 1101
 
0.4%
80.5097 1077
 
0.4%
79.0683 1071
 
0.4%
81.1822 1062
 
0.4%
76.3332 1027
 
0.3%
76.9383 1021
 
0.3%
77.677 998
 
0.3%
82.7015 976
 
0.3%
Other values (8231) 284935
96.4%
ValueCountFrequency (%)
0.0571 1
 
< 0.1%
0.0582 1
 
< 0.1%
0.0585 1
 
< 0.1%
0.0586 3
< 0.1%
0.0587 1
 
< 0.1%
0.0596 2
< 0.1%
0.0598 1
 
< 0.1%
0.0601 1
 
< 0.1%
0.0603 1
 
< 0.1%
0.0605 2
< 0.1%
ValueCountFrequency (%)
138.1101 1
 
< 0.1%
135.8172 1
 
< 0.1%
124.4448 1
 
< 0.1%
122.8846 1
 
< 0.1%
119.5851 1
 
< 0.1%
117.8584 3
 
< 0.1%
116.4568 1
 
< 0.1%
114.818 3
 
< 0.1%
113.4868 7
< 0.1%
111.9292 10
< 0.1%

R3 (MOhm)
Real number (ℝ)

Distinct8233
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.772374
Minimum0.0534
Maximum171.4839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:29.764596image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0534
5-th percentile0.1119
Q10.5988
median4.5118
Q346.3331
95-th percentile81.51
Maximum171.4839
Range171.4305
Interquartile range (IQR)45.7343

Descriptive statistics

Standard deviation28.938472
Coefficient of variation (CV)1.270771
Kurtosis-0.40596553
Mean22.772374
Median Absolute Deviation (MAD)4.3981
Skewness1.0124215
Sum6729783.1
Variance837.43517
MonotonicityNot monotonic
2022-12-20T14:09:29.925889image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83.0507 1186
 
0.4%
83.7703 1182
 
0.4%
84.6501 1145
 
0.4%
82.2033 1111
 
0.4%
81.51 1111
 
0.4%
80.6932 1079
 
0.4%
85.3974 1073
 
0.4%
80.0247 1073
 
0.4%
79.2369 1052
 
0.4%
78.592 1010
 
0.3%
Other values (8223) 284502
96.3%
ValueCountFrequency (%)
0.0534 1
< 0.1%
0.0547 1
< 0.1%
0.0553 1
< 0.1%
0.0562 1
< 0.1%
0.0567 1
< 0.1%
0.0572 1
< 0.1%
0.0576 1
< 0.1%
0.0578 2
< 0.1%
0.0579 1
< 0.1%
0.0581 1
< 0.1%
ValueCountFrequency (%)
171.4839 1
 
< 0.1%
162.3763 1
 
< 0.1%
131.01 1
 
< 0.1%
120.3335 1
 
< 0.1%
118.8647 1
 
< 0.1%
115.7553 3
 
< 0.1%
112.8031 4
 
< 0.1%
111.2549 10
 
< 0.1%
109.9965 23
< 0.1%
108.5233 44
< 0.1%

R4 (MOhm)
Real number (ℝ)

Distinct7615
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.719763
Minimum0.0404
Maximum84.5361
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:30.105380image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0404
5-th percentile0.1018
Q12.0442
median22.1943
Q335.1038
95-th percentile52.5578
Maximum84.5361
Range84.4957
Interquartile range (IQR)33.0596

Descriptive statistics

Standard deviation17.966655
Coefficient of variation (CV)0.82720311
Kurtosis-0.8371516
Mean21.719763
Median Absolute Deviation (MAD)15.9153
Skewness0.35194277
Sum6418711.2
Variance322.8007
MonotonicityNot monotonic
2022-12-20T14:09:30.263136image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.7712 1025
 
0.3%
34.5923 1013
 
0.3%
34.2691 1012
 
0.3%
34.9216 1000
 
0.3%
36.1399 993
 
0.3%
35.1038 990
 
0.3%
33.3338 986
 
0.3%
38.1853 985
 
0.3%
33.9517 985
 
0.3%
34.1241 982
 
0.3%
Other values (7605) 285553
96.6%
ValueCountFrequency (%)
0.0404 2
< 0.1%
0.0408 2
< 0.1%
0.0413 1
 
< 0.1%
0.0418 2
< 0.1%
0.0419 2
< 0.1%
0.042 1
 
< 0.1%
0.0423 2
< 0.1%
0.0424 2
< 0.1%
0.0425 3
< 0.1%
0.0426 1
 
< 0.1%
ValueCountFrequency (%)
84.5361 1
 
< 0.1%
83.6839 2
 
< 0.1%
82.6836 3
 
< 0.1%
81.8678 10
 
< 0.1%
80.9098 8
 
< 0.1%
80.1281 18
 
< 0.1%
79.2097 16
 
< 0.1%
78.4601 32
< 0.1%
77.5789 40
< 0.1%
76.8594 56
< 0.1%

R5 (MOhm)
Real number (ℝ)

Distinct7880
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.387215
Minimum0.048
Maximum126.116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:30.428324image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.048
5-th percentile0.115
Q11.8479
median33.8587
Q352.7357
95-th percentile80.3481
Maximum126.116
Range126.068
Interquartile range (IQR)50.8878

Descriptive statistics

Standard deviation27.703945
Coefficient of variation (CV)0.85539757
Kurtosis-0.99552408
Mean32.387215
Median Absolute Deviation (MAD)25.6832
Skewness0.33774941
Sum9571199.4
Variance767.50857
MonotonicityNot monotonic
2022-12-20T14:09:30.698539image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.8555 1362
 
0.5%
49.4117 1319
 
0.4%
51.7661 1312
 
0.4%
51.4875 1301
 
0.4%
50.296 1298
 
0.4%
48.6068 1297
 
0.4%
49.9804 1296
 
0.4%
51.1571 1290
 
0.4%
48.3116 1282
 
0.4%
49.1574 1281
 
0.4%
Other values (7870) 282486
95.6%
ValueCountFrequency (%)
0.048 1
 
< 0.1%
0.0483 1
 
< 0.1%
0.049 3
< 0.1%
0.0491 1
 
< 0.1%
0.0492 1
 
< 0.1%
0.0494 1
 
< 0.1%
0.0496 1
 
< 0.1%
0.0499 1
 
< 0.1%
0.05 1
 
< 0.1%
0.0502 1
 
< 0.1%
ValueCountFrequency (%)
126.116 2
 
< 0.1%
124.1949 2
 
< 0.1%
122.6378 3
 
< 0.1%
120.8197 11
 
< 0.1%
119.345 11
 
< 0.1%
117.6218 8
 
< 0.1%
116.223 26
< 0.1%
114.5874 23
< 0.1%
113.2589 56
< 0.1%
111.7044 56
< 0.1%

R6 (MOhm)
Real number (ℝ)

Distinct7867
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.215464
Minimum0.0483
Maximum159.1677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:30.876047image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0483
5-th percentile0.1239
Q11.5728
median23.8267
Q350.4951
95-th percentile79.1164
Maximum159.1677
Range159.1194
Interquartile range (IQR)48.9223

Descriptive statistics

Standard deviation27.491801
Coefficient of variation (CV)0.9410017
Kurtosis-0.89771492
Mean29.215464
Median Absolute Deviation (MAD)23.6626
Skewness0.5377608
Sum8633870.9
Variance755.79914
MonotonicityNot monotonic
2022-12-20T14:09:31.044647image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79.9474 1201
 
0.4%
80.6531 1199
 
0.4%
49.2798 1176
 
0.4%
79.1164 1167
 
0.4%
49.0116 1155
 
0.4%
50.4951 1146
 
0.4%
47.8646 1132
 
0.4%
50.2138 1127
 
0.4%
47.5609 1122
 
0.4%
48.4314 1121
 
0.4%
Other values (7857) 283978
96.1%
ValueCountFrequency (%)
0.0483 1
< 0.1%
0.0484 1
< 0.1%
0.0485 1
< 0.1%
0.0488 2
< 0.1%
0.0495 1
< 0.1%
0.0497 2
< 0.1%
0.05 2
< 0.1%
0.0501 1
< 0.1%
0.0502 2
< 0.1%
0.0503 1
< 0.1%
ValueCountFrequency (%)
159.1677 1
 
< 0.1%
125.7588 1
 
< 0.1%
118.6302 1
 
< 0.1%
116.8232 1
 
< 0.1%
115.3585 5
 
< 0.1%
113.6483 12
 
< 0.1%
112.2611 18
 
< 0.1%
110.6402 29
 
< 0.1%
109.3244 47
< 0.1%
107.7859 98
< 0.1%

R7 (MOhm)
Real number (ℝ)

Distinct7790
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.506171
Minimum0.0528
Maximum156.3368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:31.227498image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0528
5-th percentile0.1223
Q11.9488
median32.8708
Q353.3574
95-th percentile81.3453
Maximum156.3368
Range156.284
Interquartile range (IQR)51.4086

Descriptive statistics

Standard deviation27.990894
Coefficient of variation (CV)0.8610948
Kurtosis-1.0491188
Mean32.506171
Median Absolute Deviation (MAD)26.14
Skewness0.34205402
Sum9606353.6
Variance783.49017
MonotonicityNot monotonic
2022-12-20T14:09:31.393639image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.5778 1353
 
0.5%
49.9924 1336
 
0.5%
51.7898 1323
 
0.4%
49.6787 1293
 
0.4%
48.8606 1289
 
0.4%
50.8483 1275
 
0.4%
49.1134 1274
 
0.4%
53.0601 1273
 
0.4%
49.4202 1270
 
0.4%
52.7077 1260
 
0.4%
Other values (7780) 282578
95.6%
ValueCountFrequency (%)
0.0528 1
< 0.1%
0.0532 1
< 0.1%
0.0534 1
< 0.1%
0.0535 1
< 0.1%
0.054 2
< 0.1%
0.0544 1
< 0.1%
0.0547 2
< 0.1%
0.0549 1
< 0.1%
0.055 1
< 0.1%
0.0552 1
< 0.1%
ValueCountFrequency (%)
156.3368 1
 
< 0.1%
138.9553 1
 
< 0.1%
130.7453 1
 
< 0.1%
121.8976 1
 
< 0.1%
115.5214 3
 
< 0.1%
113.8957 9
 
< 0.1%
112.5752 14
 
< 0.1%
111.0301 27
< 0.1%
109.7743 61
< 0.1%
108.304 61
< 0.1%

R8 (MOhm)
Real number (ℝ)

Distinct6268
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.020719
Minimum0.0334
Maximum111.2174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:31.576499image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0334
5-th percentile0.0997
Q112.2808
median27.9494
Q342.1236
95-th percentile63.5216
Maximum111.2174
Range111.184
Interquartile range (IQR)29.8428

Descriptive statistics

Standard deviation20.513008
Coefficient of variation (CV)0.73206573
Kurtosis-0.76429631
Mean28.020719
Median Absolute Deviation (MAD)14.5317
Skewness0.18330203
Sum8280794.9
Variance420.7835
MonotonicityNot monotonic
2022-12-20T14:09:31.736794image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1005 1030
 
0.3%
47.0913 1018
 
0.3%
0.1003 1004
 
0.3%
51.6712 998
 
0.3%
47.3955 995
 
0.3%
53.0355 991
 
0.3%
46.0081 990
 
0.3%
47.6519 989
 
0.3%
49.415 989
 
0.3%
48.5445 986
 
0.3%
Other values (6258) 285534
96.6%
ValueCountFrequency (%)
0.0334 1
 
< 0.1%
0.0335 1
 
< 0.1%
0.0337 1
 
< 0.1%
0.0338 1
 
< 0.1%
0.0341 2
< 0.1%
0.0342 2
< 0.1%
0.0343 1
 
< 0.1%
0.0344 3
< 0.1%
0.0345 2
< 0.1%
0.0346 2
< 0.1%
ValueCountFrequency (%)
111.2174 1
 
< 0.1%
99.1944 1
 
< 0.1%
96.8414 1
 
< 0.1%
95.604 4
< 0.1%
94.5965 2
 
< 0.1%
93.4149 3
 
< 0.1%
92.4523 5
< 0.1%
91.3229 7
< 0.1%
90.4024 6
< 0.1%
89.3217 9
< 0.1%

R9 (MOhm)
Real number (ℝ)

Distinct6179
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.818831
Minimum0.0289
Maximum89.5884
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:31.908381image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0289
5-th percentile0.0967
Q18.3959
median22.298
Q336.6026
95-th percentile57.946
Maximum89.5884
Range89.5595
Interquartile range (IQR)28.2067

Descriptive statistics

Standard deviation18.67467
Coefficient of variation (CV)0.78402966
Kurtosis-0.69548603
Mean23.818831
Median Absolute Deviation (MAD)14.2491
Skewness0.394876
Sum7039036.3
Variance348.74331
MonotonicityNot monotonic
2022-12-20T14:09:32.064990image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0972 3137
 
1.1%
0.0973 3019
 
1.0%
0.0975 2957
 
1.0%
0.0971 2892
 
1.0%
0.097 2753
 
0.9%
0.0976 2716
 
0.9%
0.0977 2563
 
0.9%
0.0968 2526
 
0.9%
0.0978 2355
 
0.8%
0.0967 2332
 
0.8%
Other values (6169) 268274
90.8%
ValueCountFrequency (%)
0.0289 1
 
< 0.1%
0.0296 1
 
< 0.1%
0.0297 3
< 0.1%
0.0298 1
 
< 0.1%
0.0299 5
< 0.1%
0.03 4
< 0.1%
0.0301 4
< 0.1%
0.0302 3
< 0.1%
0.0303 3
< 0.1%
0.0304 3
< 0.1%
ValueCountFrequency (%)
89.5884 1
 
< 0.1%
79.4435 1
 
< 0.1%
78.6328 3
 
< 0.1%
77.9697 1
 
< 0.1%
77.1883 3
 
< 0.1%
76.5489 6
 
< 0.1%
75.7953 8
< 0.1%
75.1784 8
< 0.1%
74.4511 11
< 0.1%
73.8555 16
< 0.1%

R10 (MOhm)
Real number (ℝ)

Distinct6404
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.10688
Minimum0.0368
Maximum103.4404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:32.232608image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0368
5-th percentile0.1182
Q17.734
median23.9974
Q340.6416
95-th percentile63.7159
Maximum103.4404
Range103.4036
Interquartile range (IQR)32.9076

Descriptive statistics

Standard deviation20.868025
Coefficient of variation (CV)0.79933049
Kurtosis-0.74546228
Mean26.10688
Median Absolute Deviation (MAD)16.5172
Skewness0.41463303
Sum7715209.7
Variance435.47448
MonotonicityNot monotonic
2022-12-20T14:09:32.399202image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1199 1950
 
0.7%
0.1201 1886
 
0.6%
0.1197 1865
 
0.6%
0.1198 1864
 
0.6%
0.1202 1721
 
0.6%
0.1194 1716
 
0.6%
0.1195 1715
 
0.6%
0.1204 1632
 
0.6%
0.1205 1580
 
0.5%
0.1193 1569
 
0.5%
Other values (6394) 278026
94.1%
ValueCountFrequency (%)
0.0368 1
 
< 0.1%
0.0371 3
< 0.1%
0.0373 1
 
< 0.1%
0.0375 1
 
< 0.1%
0.0378 1
 
< 0.1%
0.038 1
 
< 0.1%
0.0385 2
< 0.1%
0.0386 1
 
< 0.1%
0.0387 2
< 0.1%
0.0388 3
< 0.1%
ValueCountFrequency (%)
103.4404 1
 
< 0.1%
92.5828 2
 
< 0.1%
91.7066 1
 
< 0.1%
90.6767 2
 
< 0.1%
89.8357 7
 
< 0.1%
88.8467 10
 
< 0.1%
88.0388 8
 
< 0.1%
87.0883 13
< 0.1%
86.3116 23
< 0.1%
85.3974 29
< 0.1%

R11 (MOhm)
Real number (ℝ)

Distinct6243
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.091068
Minimum0.0309
Maximum98.1088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:32.570913image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0309
5-th percentile0.108
Q110.630525
median27.7396
Q342.984
95-th percentile64.3359
Maximum98.1088
Range98.0779
Interquartile range (IQR)32.353475

Descriptive statistics

Standard deviation20.915791
Coefficient of variation (CV)0.74457087
Kurtosis-0.82502711
Mean28.091068
Median Absolute Deviation (MAD)15.4793
Skewness0.21238753
Sum8301584.7
Variance437.47031
MonotonicityNot monotonic
2022-12-20T14:09:32.835549image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1085 2817
 
1.0%
0.1086 2792
 
0.9%
0.1084 2771
 
0.9%
0.1088 2660
 
0.9%
0.1089 2482
 
0.8%
0.1082 2451
 
0.8%
0.1081 2222
 
0.8%
0.109 2188
 
0.7%
0.108 1895
 
0.6%
0.1092 1703
 
0.6%
Other values (6233) 271543
91.9%
ValueCountFrequency (%)
0.0309 1
 
< 0.1%
0.0311 1
 
< 0.1%
0.0312 3
< 0.1%
0.0313 2
< 0.1%
0.0316 1
 
< 0.1%
0.0317 3
< 0.1%
0.0318 1
 
< 0.1%
0.0319 3
< 0.1%
0.032 1
 
< 0.1%
0.0321 4
< 0.1%
ValueCountFrequency (%)
98.1088 1
 
< 0.1%
95.9797 1
 
< 0.1%
90.9514 1
 
< 0.1%
90.1079 2
 
< 0.1%
89.1159 5
 
< 0.1%
88.3056 20
< 0.1%
87.3522 26
< 0.1%
86.5731 36
< 0.1%
85.6562 26
< 0.1%
84.9067 46
< 0.1%

R12 (MOhm)
Real number (ℝ)

Distinct6306
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.188752
Minimum0.0336
Maximum96.173
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:33.007263image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0336
5-th percentile0.1076
Q19.8179
median26.476
Q340.2571
95-th percentile56.9212
Maximum96.173
Range96.1394
Interquartile range (IQR)30.4392

Descriptive statistics

Standard deviation19.135114
Coefficient of variation (CV)0.73066155
Kurtosis-0.82007794
Mean26.188752
Median Absolute Deviation (MAD)14.3709
Skewness0.14033781
Sum7739404.8
Variance366.1526
MonotonicityNot monotonic
2022-12-20T14:09:33.172490image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1088 1303
 
0.4%
0.1087 1247
 
0.4%
0.109 1244
 
0.4%
0.1093 1226
 
0.4%
0.1086 1223
 
0.4%
0.1091 1193
 
0.4%
0.1084 1151
 
0.4%
0.1094 1131
 
0.4%
0.1099 1108
 
0.4%
0.1095 1071
 
0.4%
Other values (6296) 283627
96.0%
ValueCountFrequency (%)
0.0336 3
< 0.1%
0.0337 1
 
< 0.1%
0.0341 1
 
< 0.1%
0.0342 2
 
< 0.1%
0.0343 3
< 0.1%
0.0344 2
 
< 0.1%
0.0346 3
< 0.1%
0.0347 2
 
< 0.1%
0.035 4
< 0.1%
0.0351 5
< 0.1%
ValueCountFrequency (%)
96.173 1
 
< 0.1%
90.2894 1
 
< 0.1%
88.4834 1
 
< 0.1%
87.5281 2
 
< 0.1%
86.7475 1
 
< 0.1%
85.8287 5
 
< 0.1%
85.0777 8
 
< 0.1%
84.1934 10
 
< 0.1%
83.4702 26
< 0.1%
82.6184 33
< 0.1%

R13 (MOhm)
Real number (ℝ)

Distinct6389
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.004212
Minimum0.0338
Maximum98.2095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:33.341959image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0338
5-th percentile0.1011
Q17.8857
median22.0497
Q335.3528
95-th percentile54.173
Maximum98.2095
Range98.1757
Interquartile range (IQR)27.4671

Descriptive statistics

Standard deviation17.653981
Coefficient of variation (CV)0.76742385
Kurtosis-0.69999399
Mean23.004212
Median Absolute Deviation (MAD)13.543
Skewness0.3275863
Sum6798296.7
Variance311.66304
MonotonicityNot monotonic
2022-12-20T14:09:33.508074image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1031 1213
 
0.4%
0.103 1201
 
0.4%
0.1029 1173
 
0.4%
0.1026 1151
 
0.4%
0.1027 1148
 
0.4%
0.1032 1133
 
0.4%
0.1034 1085
 
0.4%
0.1025 1081
 
0.4%
0.1035 1075
 
0.4%
0.1038 1075
 
0.4%
Other values (6379) 284189
96.2%
ValueCountFrequency (%)
0.0338 1
 
< 0.1%
0.0339 1
 
< 0.1%
0.0341 1
 
< 0.1%
0.0342 2
< 0.1%
0.0343 2
< 0.1%
0.0345 1
 
< 0.1%
0.0348 1
 
< 0.1%
0.0349 2
< 0.1%
0.035 3
< 0.1%
0.0351 1
 
< 0.1%
ValueCountFrequency (%)
98.2095 1
 
< 0.1%
93.9967 2
 
< 0.1%
78.7567 1
 
< 0.1%
76.7411 2
 
< 0.1%
76.0113 3
 
< 0.1%
75.4135 3
 
< 0.1%
74.7083 9
 
< 0.1%
74.1305 18
< 0.1%
73.4487 21
< 0.1%
72.8899 28
< 0.1%

R14 (MOhm)
Real number (ℝ)

Distinct6195
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.017023
Minimum0.0319
Maximum99.8467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-12-20T14:09:33.678374image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0319
5-th percentile0.1071
Q19.723975
median27.3206
Q345.285
95-th percentile68.9791
Maximum99.8467
Range99.8148
Interquartile range (IQR)35.561025

Descriptive statistics

Standard deviation22.438188
Coefficient of variation (CV)0.77327671
Kurtosis-0.90551839
Mean29.017023
Median Absolute Deviation (MAD)17.7033
Skewness0.29742818
Sum8575226.8
Variance503.47229
MonotonicityNot monotonic
2022-12-20T14:09:33.845346image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1078 2555
 
0.9%
0.1077 2546
 
0.9%
0.1079 2538
 
0.9%
0.1075 2525
 
0.9%
0.1082 2473
 
0.8%
0.108 2445
 
0.8%
0.1074 2403
 
0.8%
0.1083 2267
 
0.8%
0.1072 2192
 
0.7%
0.1071 1938
 
0.7%
Other values (6185) 271642
91.9%
ValueCountFrequency (%)
0.0319 1
 
< 0.1%
0.0322 1
 
< 0.1%
0.0324 2
< 0.1%
0.0325 3
< 0.1%
0.0326 1
 
< 0.1%
0.0327 1
 
< 0.1%
0.0328 3
< 0.1%
0.0329 1
 
< 0.1%
0.033 1
 
< 0.1%
0.0332 2
< 0.1%
ValueCountFrequency (%)
99.8467 1
 
< 0.1%
90.595 1
 
< 0.1%
88.7468 2
 
< 0.1%
87.7697 2
 
< 0.1%
86.9716 2
 
< 0.1%
86.0327 4
 
< 0.1%
85.2654 6
 
< 0.1%
84.3623 9
 
< 0.1%
83.6241 26
< 0.1%
82.7549 47
< 0.1%

Interactions

2022-12-20T14:09:20.507055image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:12.564175image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.010279image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.664555image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.908100image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.442146image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.882591image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.486362image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.006560image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.634984image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:44.322585image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:47.753052image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:51.461170image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.207627image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:58.962897image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:02.507628image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.036162image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:09.507015image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.060312image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:16.690506image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:20.724556image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:12.740949image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.166905image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.817482image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.068471image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.595585image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:30.046394image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.648098image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.180313image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.805551image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:44.485704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:48.105887image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:51.638553image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.383309image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:59.143057image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:02.665890image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.196363image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:09.668676image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.225167image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:16.879909image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:20.923755image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:12.906003image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.348829image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.997207image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.250156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.772165image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:30.229662image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.827214image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.375815image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.998019image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:44.669989image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:48.279078image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:51.837023image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.572894image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:59.326769image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:02.853377image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.379199image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:09.857755image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.411045image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:17.128479image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:21.121463image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:13.049890image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.515979image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.152409image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.417901image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.937961image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:30.511670image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.995903image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.556338image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:41.174939image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:44.832881image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:48.453993image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.016390image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.749846image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:59.500237image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.026478image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.547620image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:10.028516image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.579593image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:17.323433image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:21.324333image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:13.448473image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.689786image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.319433image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.599917image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:27.142547image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:30.681864image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:34.176228image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.762291image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:41.361013image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.021397image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:48.640401image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.206980image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.940473image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:59.686208image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.226034image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.730945image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:10.318787image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.759314image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:17.507819image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:21.503964image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:13.609032image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:16.860205image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.474062image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.767198image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:27.298723image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:30.848077image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:34.346144image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:37.936949image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:41.535060image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.187137image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:48.810356image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.388068image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:56.126762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:59.866548image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.390875image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:06.903630image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:10.476361image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:13.934636image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:17.678500image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:21.685518image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:13.769130image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.038828image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.646819image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:23.953870image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:27.473971image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.034539image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:34.525050image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:38.131166image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:41.723251image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.370046image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.003173image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.574599image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:56.316337image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.054536image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.569391image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.090108image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:10.656399image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.116208image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:17.857612image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:21.870109image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:13.926288image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.211324image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.803671image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:24.134422image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:27.681067image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.208264image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:34.699841image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:38.319505image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.015394image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.536439image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.176013image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.763484image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:56.500944image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.228737image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.738036image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.262042image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:10.835038image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.288550image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:18.032352image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.049863image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.089324image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.411631image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:20.972733image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:24.402965image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:27.855934image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.386204image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:34.875273image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:38.522889image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.179502image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.709271image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.355639image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:52.944725image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:56.685615image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.412603image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:03.918030image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.443102image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.011362image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.466540image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:18.280245image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.237529image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.251884image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.608307image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.137073image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:24.578409image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.035280image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.568007image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.054417image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:38.707738image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.365312image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:45.882242image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.537694image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:53.135391image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:56.873789image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.593629image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:04.105496image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.624341image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.195665image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.648776image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:18.514479image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.400890image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.400405image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.764666image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.290167image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:24.738300image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.193082image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.731854image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.218146image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:38.880757image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.533884image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.045026image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.702260image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:53.306098image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.041698image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.753928image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:04.268450image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.790460image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.358960image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.807101image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:18.685003image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.575345image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.555921image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:17.948223image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.452970image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:24.918624image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.373002image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:31.913056image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.390248image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.062384image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.712570image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.211029image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:49.881830image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:53.593434image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.225283image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:00.938475image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:04.435565image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:07.966334image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.526771image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:14.985578image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:18.858380image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.762291image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.721888image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:18.234477image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.626979image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.101609image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.548537image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.097380image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.568381image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.246859image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:42.906292image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.395456image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.072116image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:53.773439image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.417188image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.122498image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:04.722523image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.148109image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.708460image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:15.171163image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.062823image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:22.940868image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:14.887025image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:18.412079image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.797302image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.287227image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.729200image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.281737image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.750664image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.434807image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.093632image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.577222image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.255826image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:53.966837image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.610792image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.306167image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:04.890285image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.332756image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:11.896998image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:15.355606image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.251590image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:23.213657image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.044241image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:18.574916image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:21.953590image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.448915image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:28.892017image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.443562image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:35.912454image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.604979image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.268561image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.748079image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.430500image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:54.143527image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.794250image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.475465image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.052407image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.499116image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.063559image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:15.548483image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.422033image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:23.380356image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.191971image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:18.739370image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.108623image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.610340image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.058476image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.613068image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:36.183602image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.774331image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.435315image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:46.903083image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.596235image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:54.319160image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:57.971539image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.641759image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.215086image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.659200image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.227069image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:15.712728image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.605143image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:23.543934image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.385695image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:18.895776image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.273056image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.777732image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.224051image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.781595image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:36.335873image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:39.948274image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.606507image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:47.068164image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.768826image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:54.497941image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:58.156440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.812246image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.379835image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.829162image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.395773image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:15.883933image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.776396image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:23.715344image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.546608image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.178374image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.427451image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:25.939655image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.386776image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:32.953378image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:36.501664image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.118603image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.779238image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:47.234314image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:50.940903image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:54.670997image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:58.336663image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:01.983090image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.545472image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:08.997489image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.566374image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:16.046159image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:19.962683image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:23.887347image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.703944image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.332414image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.585851image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.102383image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.552611image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.136823image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:36.671296image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.291628image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:43.960412image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:47.400263image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:51.118079image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:54.847708image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:58.620905image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:02.158780image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.706765image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:09.169078image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.727058image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:16.306234image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:20.135076image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:24.064906image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:15.855042image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:19.498904image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:22.743212image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:26.270583image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:29.719223image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:33.315822image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:36.836444image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:40.462588image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:44.147829image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:47.594853image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:51.291199image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:55.034837image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:08:58.785874image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:02.336905image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:05.872555image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:09.340834image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:12.892717image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:16.492994image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2022-12-20T14:09:20.316688image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2022-12-20T14:09:34.008301image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:
  • Variable_type-Variable_type : Method, Range
  • Categorical-Categorical : Cramer's V, [0,1]
  • Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
  • Numerical-Numerical : Spearman's ρ, [-1,1]
The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.
2022-12-20T14:09:34.293730image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-12-20T14:09:34.575726image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-12-20T14:09:34.860446image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-12-20T14:09:35.247082image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-12-20T14:09:24.343949image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-12-20T14:09:25.247621image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Time (s)CO (ppm)Humidity (%r.h.)Temperature (C)Flow rate (mL/min)Heater voltage (V)R1 (MOhm)R2 (MOhm)R3 (MOhm)R4 (MOhm)R5 (MOhm)R6 (MOhm)R7 (MOhm)R8 (MOhm)R9 (MOhm)R10 (MOhm)R11 (MOhm)R12 (MOhm)R13 (MOhm)R14 (MOhm)
00.0000.049.730026.4600242.43040.89800.08760.14360.12090.10470.11920.12720.12820.10870.09980.12170.11150.11530.10800.1102
10.3100.049.730026.4600241.41220.89800.08910.14490.12310.10580.12100.12800.12990.10900.09980.12190.11130.11520.10800.1102
20.6190.049.730026.4600241.12210.89810.09040.14620.12490.10690.12250.12900.13140.10880.09960.12200.11120.11490.10830.1102
30.9270.049.730026.4600240.83290.89800.09170.14750.12670.10770.12390.12960.13280.10900.09960.12200.11100.11510.10800.1100
41.2360.049.730126.4605240.55700.89800.09270.14880.12790.10840.12530.13040.13380.10900.09960.12190.11090.11490.10820.1099
51.5440.049.733226.4728240.63530.89840.09360.14960.12950.10920.12620.13120.13500.10900.09950.12190.11090.11480.10830.1099
61.8530.049.736326.4852240.71380.89800.09460.15050.13040.10990.12720.13170.13590.10900.09940.12190.11070.11470.10820.1100
72.1610.049.739426.4975240.79200.89870.09510.15150.13140.11050.12820.13230.13650.10900.09950.12170.11050.11470.10840.1099
82.4680.049.740026.5000240.79290.89810.09600.09440.15010.11670.19030.22050.33500.05070.05570.09440.15370.34330.58610.6708
92.7780.049.740026.5000240.77370.21590.48871.32462.23661.60182.34272.68033.58523.65593.79654.75457.818011.458112.855716.7909
Time (s)CO (ppm)Humidity (%r.h.)Temperature (C)Flow rate (mL/min)Heater voltage (V)R1 (MOhm)R2 (MOhm)R3 (MOhm)R4 (MOhm)R5 (MOhm)R6 (MOhm)R7 (MOhm)R8 (MOhm)R9 (MOhm)R10 (MOhm)R11 (MOhm)R12 (MOhm)R13 (MOhm)R14 (MOhm)
29551490906.8100.061.2726.30.59580.200045.633251.591153.167528.179750.296049.605555.084670.125453.792964.141662.498056.921251.245358.5835
29551590907.1170.061.2726.30.15400.200040.887948.164953.465427.962551.766147.864649.420262.538553.792967.664667.869756.921248.662867.8952
29551690907.4270.061.2726.30.00000.199437.819345.633248.411226.923545.760546.239648.860666.068953.105562.309261.225056.188938.219267.8952
29551790907.7350.061.2726.30.00000.200035.487540.297548.117126.832748.068245.955746.239560.659755.221465.098167.869755.474948.117866.8445
29551890908.0440.061.2726.30.00000.199733.539435.621644.885826.248344.812544.943346.741573.234153.792962.309260.379157.672548.914668.3837
29551990908.3530.061.2726.30.00000.200031.425930.523041.830125.408444.352743.044345.748063.521656.377564.141661.617356.188948.914667.8952
29552090908.6630.061.2726.30.00000.200029.369925.311439.517425.408443.027342.593945.266763.978655.964163.715959.482055.797247.584668.3837
29552190908.9710.061.2726.30.00000.199225.228320.195535.273725.771541.999141.526444.085062.014857.946060.577266.834954.778548.117868.3837
29552290909.2790.061.2726.30.00000.200022.027615.576431.944124.542742.185837.135043.198059.761458.763064.141658.682555.474947.298668.3837
29552390909.5880.061.2726.30.00000.200018.672211.730827.839424.711241.196240.073843.436560.659757.151259.746259.927254.099147.062967.3181